weber2017localization

Abstract

Every year snow avalanches cause damages to buildings and to infrastructure. In order to setup protective measures, scientists rely on exact avalanche models allowing to predict and simulate the flows and dynamics of avalanches. However, the modeling of the inner dynamics constitutes still a challenging task, as conventional techniques are limited to static observations at the surface of avalanches. Therefore, a technique is required allowing to continuously monitor avalanches from within. One way of examining the inner dynamics of avalanches is to place several small wireless sensor nodes into them. Wireless sensor nodes are used in a wide variety of areas allowing to monitor different physical and environmental properties - also under dangerous conditions. Thus, by continuously tracking each sensor node's position, conclusions on the inner flows of the avalanches can be drawn. Several techniques already exist for measuring a sensor node's position. As a first step, to determine which of these techniques are suited for the usage in avalanches, different localization methods are verified in the course of this thesis for their usability under snowy conditions. To this end, firstly, different localization are reviewed and then the two most promising methods are implemented into software, namely a RSSI and a TOF based approach. The conducted experiments show, that both techniques can be used in snow. The highest accuracy was thereby achieved with the TOF based approach, namely a ranging error of 0.77 m to 2.26 m in average. Using RSSI, by contrast, the average localization error amounted to 3.74 m. Accordingly, a TOF based approach appears as a promising technique for the examination of avalanches.

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